Convolutional neural networks and the modulation transfer function

Page King; R. John Koshel

doi:10.1117/12.2672623

10 October 2023 Convolutional neural networks and the modulation transfer function

Page King, R. John Koshel

Proceedings Volume 12675, Applications of Machine Learning 2023; 1267509 (2023) https://doi.org/10.1117/12.2672623
Event: SPIE Optical Engineering + Applications, 2023, San Diego, California, United States

Abstract

Convolutional neural networks yield activations from spatial frequency content in an image, allowing them to learn and recognize features of classification targets. This paper explores the spatial frequency response of CNNs in the context of an imaging system's modulation transfer function. Deriving the relationship between CNN design and imaging system design is a fundamental first step in optimizing these systems at the system level.

Conference Presentation

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Page King and R. John Koshel "Convolutional neural networks and the modulation transfer function", Proc. SPIE 12675, Applications of Machine Learning 2023, 1267509 (10 October 2023); https://doi.org/10.1117/12.2672623

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